In this paper by electromagnetic modeling of neurons in Brain, the Brain Waves have been derived in a full-Wave way. Now, in all clinics and research centers, traditionally, it has been done by using the quasi-static approximation of the Maxwell equation in electromagnetic. However, the error rate resulting from the approximation has not been studied upon the final results. This issue becomes more noticeable due to increasing the sensitivity of today's modern sensors. In this paper, first, with an overview of the basics of applying quasi-static approximation in the analysis Brain Waves, ambiguities about the suitability of this approximation are presented and the necessity of full-Wave solution of the problem is expressed. Then, in the simplest form, the electromagnetic fields aroused from a current dipole where is located in the center of a sphere with known conductivity is written in terms of Bessel and Hankel function expansion; and the problem has been solved in a full-Wave way by using of scattering theories in electromagnetic. Finally, the curve of relative difference measure (RDM) between quasi-static and full-Wave solution has been drawn in terms of frequency conductivity. One of the important achievements of full-Wave modeling is enriching the information resulted from EEG and MEG and consequently extracting more accurate patterns from Brain activities.

Introduction: Military operations have become more complex and require cognitive readiness to adapt to the conditions that match the individual's Brain reactions. The research aims to investigate the impact of cognitive readiness training on Brain Wave patterns.Method: The research was quasi-experimental with a control group and pretest-posttest design. The population included military officers that 38 members. Furthermore, Operational Strategic Management Simulation (OSMS) and the Quantitative Electroencephalogram (QEEG) was used. Moreover, a 40-session cognitive readiness course was provided for the experimental group, and an 11-session course was presented for the control group. Data were analyzed using the MANCOVA test.Results: Cognitive readiness training reduces beta and delta Waves in the frontal and central regions. This training increase in the alpha and theta Waves in all of Brain area (p<0.01). Also, sLORETA showed that the maximum change was observed in the alpha Wave in the dorsolateral prefrontal cortex. Conclusion: By promoting cognitive readiness, individuals can make better decisions, optimize performance, and minimize cognitive and emotional burdens. Implementing tools like QEEG assessments can provide insights into individual differences and abilities, aiding in task suitability evaluation.Embracing cognitive readiness can ultimately help reduce human errors, enhance independence, and improve performance in high-stress military environments.

The collaborative Brain Initiative (Brain Research through Advancing Innovative Neurotechnologies) was launched according to the aims of Brain Activity Map (BAM) on April, 2, 2013, with the main goal of mapping the activity of every neuron and cell in the human Brain. The Brain Initiative will be led in a synergistic activity by prominent scientific foundations and institutes in U.S.A, such as the National Institutes of Health (NIH) and the National Science Foundation (NSF), and the private sector. The ultimate goal of this initiative is “to accelerate the development and application of innovative technologies to construct a dynamic picture of Brain function that integrates neuronal and circuit activity over time and space”. Undoubtedly, through the Brain Initiative we can understand how the interplay of fluctuating patterns of electrical and chemical activity flowing within neural circuits creates our unique cognitive and behavioral capabilities. This attempt of the initiative is to follow an interdisciplinary approach and the development and creation of novel neurotechnologies and neuroimaging tools. The outcome will be generation of big data and a huge cybernetic platform which might be transformative for better diagnostic and therapeutics for millions worldwide who suffer from Brain disorders. The Brain Initiative has been linked to the successful Apollo Space and Human Genome Project.

Introduction: Research evidence indicates that maladaptive reorganization of the Brain plays a critical role in amplifying pain experiences and pain chronification,however, no clear evidence of change exists in Brain Wave activity among patients with chronic low back pain (CLBP). The objective of this study was to assess Brain Wave activity in patients with CLBP, compared to healthy controls. Methods: Twenty-five patients with CLBP and twenty-four healthy controls participated in the study. A quantitative electroencephalography device was used to assess Brain Wave activity in eyes-open and eyes-closed (EO and EC) conditions. The regional absolute and relative power of Brain Waves were compared between the groups. Results: Our results showed a significant increase in the absolute power of theta (F=5. 905, P=0. 019), alpha (F=5. 404, P=0. 024) Waves in patients with CLBP compared to healthy subjects in both EC and EO conditions. Patients with CLBP showed a reduced delta absolute power in the frontal region (F=5. 852, P=0. 019) and augmented delta absolute power in the central region (F=5. 597, P=0. 022) in the EO condition. An increased delta absolute power was observed in the frontal (F=7. 563 P=0. 008), central (F=10. 430, P=0. 002), and parietal (F=4. 596, P=0. 037) regions in patients with CLBP compared to the healthy subjects in the EC condition. In the EC condition, significant increases in theta relative power (F=4. 680, P=0. 036) in the parietal region were also found in patients with CLBP. Conclusion: The increased absolute power of Brain Waves in people with CLBP may indicate cortical overactivity and changes in the pain processing mechanisms in these patients.

Charge and spin transport properties of a clean $SNS$ Josephson junction (triplet superconductor-normal metal-triplet superconductor) are studied using the quasiclassical Eilenberger equation of Green’s function. Our system consists of two p-Wave superconducting crystals separated by a Copper nano layer. Effects of thickness of normal layer between superconductors on the spin and charge currents are investigated. Also misorientation between triplet superconductors which creates the spin current is another subject of this paper.